Artificial Intelligence (AI) in Drug Discovery Market – Thematic Research

Explore trends and insights from the following data in the ‘Artificial Intelligence (AI) in Drug Discovery Market’ thematic report: 

• Understanding the key trends impacting the theme over the next 12 to 24 months. 
• Comprehensive analysis of drugs discovered using AI and survey data on the adoption of AI in pharma. 
• Detailed value chain breaks down Artificial Intelligence (AI) in the Drug Discovery Market into Target Identification and Validation, Generation of Molecule Leads/De Novo Drug Design, Drug Repurposing, and Response Biomarker Discovery. 
• Overview of the current landscape, as well as key players (Microsoft, Alphabet, AbCellera, Atomwise, and IBM among others). 
• Highlight opportunities for the use of AI in the future.  
• Offer a sector scorecard to predict leading companies within each sector. Our sector scorecards have three screens: a thematic screen, a valuation screen, and a risk screen.  

How is the ‘Artificial Intelligence (AI) in Drug Discovery Market’ report different from other reports in the market? 

Corporate giants, governments, and individuals across all industry verticals are adapting to new technologies that will accelerate growth in the coming decade. Getting access to the Artificial Intelligence (AI) in Drug Discovery Market thematic report today will help you to: 

• See who the leading players are in the AI in drug discovery space. 
• See how the competitive landscape is evolving, with a review of company activity including strategic partnerships and funding deals, as well as mergers and acquisitions (M&A). 

• See what trends are driving the use of AI in drug discovery. 
• See an analysis of drugs discovered by AI, including by company, phase of development, therapy area, and molecule type. 

We recommend this valuable source of information to anyone involved in: 

• ​Pharma Manufacturers (Innovative, Biotech, Generics, Biosimilars, Rare/Orphan Disease /Distributors/ Pharmacies/Big Pharma, Small Biotech, Start-Ups, etc.), 
• Parallel Trade Organisations 
• Clinical Research Organisations (CROs) 
• Financial Institutions (Investors in Pharma/Biotech, Pricing Consultancies) 
• Healthcare Organisations (Payers, HTA Bodies, Reimbursement Groups, Government Healthcare Organizations) 

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AI in Drug Discovery Market Overview

In recent years, the pharma industry has undergone increased levels of digital transformation, driven by the COVID-19 pandemic. The availability of ultra-large datasets and technological advances has led to more interest in the application of AI and big data analytics across the pharma value chain, including drug discovery, clinical trial design, and sales and marketing. Several start-ups have emerged which are interested in the use of AI in drug discovery. This has led to an increasing number of drug discovery partnerships and record levels of investment. While most drugs developed using AI are in the early stages of development, there have been some recent major milestones, including the first drug developed by AI to enter clinical trials and the repurposing of an already-marketed drug to treat COVID-19.

The artificial intelligence in drug discovery thematic intelligence report assesses provides an overview of the current landscape, including healthcare, technology, regulatory, and macroeconomic trends, as well as key players, while also highlighting opportunities for the use of AI in the future. Furthermore, it provides an industry-specific analysis based on GlobalData databases and surveys, as well as several case studies.

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AI in Drug Discovery Market Trends

The key trends that will shape the AI in drug discovery theme can be classified into four categories: healthcare trends, technology trends, macroeconomic trends, and regulatory trends.

• Healthcare trends – The key healthcare trends that will shape the AI in drug discovery theme are COVID-19 on digital transformation in pharma, the rising cost of R&D and dwindling pipelines, increasing availability of ultra-large datasets, increased need for open science in drug discovery, pharma companies building in-house AI capabilities, formation of industry consortia in AI, and role of AI in precision and personalized medicine.

• Technology trends – The report focuses on key technology trends impacting AI in drug discovery theme including the role of technology giants in AI-based drug discovery, big data, cloud, quantum computing, and cybersecurity.

• Macroeconomic trends – The key macroeconomic trends that will shape the AI in drug discovery theme are addressing AI skills shortages, increased AI partnerships in drug discovery, increased volume and value of AI-related funding deals in drug discovery, mergers and acquisitions (M&As), and China’s quest for AI dominance.

• Regulatory trends – The report highlights the key regulatory trends shaping the AI in drug discovery theme including the International Coalition of Medicines Regulatory Authorities (ICMRA) report on the use of AI to develop drugs, regulatory divergence, the European Commission (EC) white paper, and the proposed framework on AI, and the US leadership in AI. 

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AI in Drug Discovery – Industry Analysis

The pharma industry is slow when adopting new technologies such as AI. However, there has been increased activity over the past few years. Many more companies, including recognized leaders, are adopting AI as part of their digital transformation strategies. AI will be a key driver of healthcare innovation in the future through various applications that include management of chronic diseases, drug discovery and development, improvement of clinical trials, manufacturing, and supply chains. COVID-19 has been one of the reasons for the rapid innovation and investment in AI. Compared to pharma and medical device companies, GlobalData forecasts that healthcare providers will spend the most on AI platforms in 2024.

The AI in drug discovery market analysis also covers:

• Analysis of drugs discovered using AI
• Survey data on the adoption of AI in pharma
• Deals
• Case studies
• Hiring trends
• Company filing trends
• Social media trends

Global AI Platform Revenue in Pharma, Medical, and Healthcare, 2019-2024

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AI in Drug Discovery - Value Chain Analysis

The main applications of AI algorithms in drug discovery are the identification and validation of drug targets, virtual screening of compounds, de novo drug design, drug repurposing, and identification of treatment response biomarkers.

Drug discovery begins with the identification of drug targets, which are molecules that are inherently linked to a particular disease process. They should exhibit several features such as involvement in a crucial biological pathway, functionally and structurally characterized, and the ability to interact with drug-like compounds.

AI in Drug Discovery Value Chain

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Leading AI Technology Vendors

Some of the leading technology vendors within the AI in drug discovery theme are:

• Microsoft
• Alphabet
• IBM

Leading AI Specialists in Drug Discovery

Some of the leading AI specialists in drug discovery are:

• AbCellera
• Atomwise
• Auransa

Leading Pharma Adopters of AI in Drug Discovery

Some of the leading pharma adopters of AI in drug discovery are:

• AstraZeneca
• Bristol Myers Squibb
• GSK

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Drug Development Scorecard – AI Theme

At GlobalData, we use a scorecard approach to predict tomorrow’s leading companies within each sector. Our sector scorecards have three screens: a thematic screen, a valuation screen, and a risk screen. The drug development scorecard has two screens:

• The thematic screen tells us who are the overall leaders in the 10 themes that matter most, based on our thematic engine.
• The valuation screen ranks our universe of companies within a sector based on selected valuation metrics.

Drug Development Scorecard: Thematic Screen

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